{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "'''\n",
    "【项目03】  知乎数据清洗整理和结论研究\n",
    "\n",
    "作业要求：\n",
    "1、数据清洗 - 去除空值\n",
    "要求：创建函数\n",
    "提示：fillna方法填充缺失数据，注意inplace参数\n",
    "\n",
    "2、问题1 知友全国地域分布情况，分析出TOP20\n",
    "要求：\n",
    "① 按照地域统计 知友数量、知友密度（知友数量/城市常住人口），不要求创建函数\n",
    "② 知友数量，知友密度，标准化处理，取值0-100，要求创建函数\n",
    "③ 通过多系列柱状图，做图表可视化\n",
    "提示：\n",
    "① 标准化计算方法 = (X - Xmin) / (Xmax - Xmin)\n",
    "② 可自行设置图表风格\n",
    "\n",
    "3、问题2 知友全国地域分布情况，分析出TOP20\n",
    "要求：\n",
    "① 按照学校（教育经历字段） 统计粉丝数（‘关注者’）、关注人数（‘关注’），并筛选出粉丝数TOP20的学校，不要求创建函数\n",
    "② 通过散点图 → 横坐标为关注人数，纵坐标为粉丝数，做图表可视化\n",
    "③ 散点图中，标记出平均关注人数（x参考线），平均粉丝数（y参考线）\n",
    "提示：\n",
    "① 可自行设置图表风格\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        _id  关注的收藏夹   关注  关注者  关注的问题  关注的话题  关注的专栏   职业1  \\\n",
      "0  587598f89f11daf90617fb7a      52   17    1     30     58      2  交通仓储   \n",
      "1  587598f89f11daf90617fb7c      27   73   15     87     26      1  高新科技   \n",
      "2  587598f89f11daf90617fb7e      72   94    1    112     20      4   NaN   \n",
      "3  587598f89f11daf90617fb80     174   84    8    895     30      7    金融   \n",
      "4  587598f89f11daf90617fb82       3  236   64    119     44     17    金融   \n",
      "\n",
      "    职业2    回答   提问    收藏       个人简介  居住地  所在行业                       教育经历 职业经历  \n",
      "0    邮政   0.0  0.0   3.0        NaN  NaN    邮政                        NaN  NaN  \n",
      "1   互联网  56.0  4.0  14.0        NaN   重庆   互联网                     重庆邮电大学  NaN  \n",
      "2   NaN   1.0  0.0  21.0        NaN  NaN   NaN                        NaN  NaN  \n",
      "3    财务   0.0  0.0  22.0        NaN  NaN    财务                        NaN  NaN  \n",
      "4  证券投资   6.0  0.0  12.0  无求 心静 魔不生   上海  证券投资  雪城大学（Syracuse University）  NaN  \n",
      "     省   地区 结尾        常住人口\n",
      "0  安徽省  安徽省  省  59500468.0\n",
      "1  安徽省  安庆市  市   5311379.0\n",
      "2  安徽省  蚌埠市  市   3164467.0\n",
      "3  安徽省  亳州市  市   4850657.0\n",
      "4  安徽省  巢湖市  市   3873102.0\n"
     ]
    }
   ],
   "source": [
    "# 数据读取\n",
    "\n",
    "data1 = pd.read_csv('C:/Users/Hjx/Desktop/知乎数据_201701.csv', engine = 'python')\n",
    "data2 = pd.read_csv('C:/Users/Hjx/Desktop/六普常住人口数.csv', engine = 'python')\n",
    "print(data1.head())\n",
    "print(data2.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_id</th>\n",
       "      <th>关注的收藏夹</th>\n",
       "      <th>关注</th>\n",
       "      <th>关注者</th>\n",
       "      <th>关注的问题</th>\n",
       "      <th>关注的话题</th>\n",
       "      <th>关注的专栏</th>\n",
       "      <th>职业1</th>\n",
       "      <th>职业2</th>\n",
       "      <th>回答</th>\n",
       "      <th>提问</th>\n",
       "      <th>收藏</th>\n",
       "      <th>个人简介</th>\n",
       "      <th>居住地</th>\n",
       "      <th>所在行业</th>\n",
       "      <th>教育经历</th>\n",
       "      <th>职业经历</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>587598f89f11daf90617fb7a</td>\n",
       "      <td>52</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>58</td>\n",
       "      <td>2</td>\n",
       "      <td>交通仓储</td>\n",
       "      <td>邮政</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>邮政</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>587598f89f11daf90617fb7c</td>\n",
       "      <td>27</td>\n",
       "      <td>73</td>\n",
       "      <td>15</td>\n",
       "      <td>87</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>高新科技</td>\n",
       "      <td>互联网</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>重庆</td>\n",
       "      <td>互联网</td>\n",
       "      <td>重庆邮电大学</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>587598f89f11daf90617fb7e</td>\n",
       "      <td>72</td>\n",
       "      <td>94</td>\n",
       "      <td>1</td>\n",
       "      <td>112</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>587598f89f11daf90617fb80</td>\n",
       "      <td>174</td>\n",
       "      <td>84</td>\n",
       "      <td>8</td>\n",
       "      <td>895</td>\n",
       "      <td>30</td>\n",
       "      <td>7</td>\n",
       "      <td>金融</td>\n",
       "      <td>财务</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>财务</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>587598f89f11daf90617fb82</td>\n",
       "      <td>3</td>\n",
       "      <td>236</td>\n",
       "      <td>64</td>\n",
       "      <td>119</td>\n",
       "      <td>44</td>\n",
       "      <td>17</td>\n",
       "      <td>金融</td>\n",
       "      <td>证券投资</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>无求 心静 魔不生</td>\n",
       "      <td>上海</td>\n",
       "      <td>证券投资</td>\n",
       "      <td>雪城大学（Syracuse University）</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>587598f89f11daf90617fb84</td>\n",
       "      <td>15</td>\n",
       "      <td>577</td>\n",
       "      <td>46</td>\n",
       "      <td>7472</td>\n",
       "      <td>131</td>\n",
       "      <td>81</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>587598f89f11daf90617fb86</td>\n",
       "      <td>13</td>\n",
       "      <td>52</td>\n",
       "      <td>3</td>\n",
       "      <td>47</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>大王叫我来巡山。</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>587598f89f11daf90617fb88</td>\n",
       "      <td>105</td>\n",
       "      <td>104</td>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>46</td>\n",
       "      <td>13</td>\n",
       "      <td>高新科技</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>山东</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>587598f89f11daf90617fb8a</td>\n",
       "      <td>795</td>\n",
       "      <td>268</td>\n",
       "      <td>39</td>\n",
       "      <td>49</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "      <td>高新科技</td>\n",
       "      <td>互联网</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>互联网</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>587598f89f11daf90617fb8c</td>\n",
       "      <td>8</td>\n",
       "      <td>111</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "      <td>缺失数据</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        _id  关注的收藏夹   关注  关注者  关注的问题  关注的话题  关注的专栏   职业1  \\\n",
       "0  587598f89f11daf90617fb7a      52   17    1     30     58      2  交通仓储   \n",
       "1  587598f89f11daf90617fb7c      27   73   15     87     26      1  高新科技   \n",
       "2  587598f89f11daf90617fb7e      72   94    1    112     20      4  缺失数据   \n",
       "3  587598f89f11daf90617fb80     174   84    8    895     30      7    金融   \n",
       "4  587598f89f11daf90617fb82       3  236   64    119     44     17    金融   \n",
       "5  587598f89f11daf90617fb84      15  577   46   7472    131     81  缺失数据   \n",
       "6  587598f89f11daf90617fb86      13   52    3     47      2      6  缺失数据   \n",
       "7  587598f89f11daf90617fb88     105  104    2     55     46     13  高新科技   \n",
       "8  587598f89f11daf90617fb8a     795  268   39     49      1     69  高新科技   \n",
       "9  587598f89f11daf90617fb8c       8  111    3     31      6      3  缺失数据   \n",
       "\n",
       "    职业2    回答   提问    收藏       个人简介   居住地  所在行业                       教育经历  \\\n",
       "0    邮政   0.0  0.0   3.0       缺失数据  缺失数据    邮政                       缺失数据   \n",
       "1   互联网  56.0  4.0  14.0       缺失数据    重庆   互联网                     重庆邮电大学   \n",
       "2  缺失数据   1.0  0.0  21.0       缺失数据  缺失数据  缺失数据                       缺失数据   \n",
       "3    财务   0.0  0.0  22.0       缺失数据  缺失数据    财务                       缺失数据   \n",
       "4  证券投资   6.0  0.0  12.0  无求 心静 魔不生    上海  证券投资  雪城大学（Syracuse University）   \n",
       "5  缺失数据   0.0  0.0  21.0       缺失数据  缺失数据  缺失数据                       缺失数据   \n",
       "6  缺失数据   0.0  0.0   0.0   大王叫我来巡山。  缺失数据  缺失数据                       缺失数据   \n",
       "7  电子商务   0.0  0.0   0.0       缺失数据    山东  电子商务                       缺失数据   \n",
       "8   互联网   0.0  0.0   0.0       缺失数据  缺失数据   互联网                       缺失数据   \n",
       "9  缺失数据   0.0  0.0   2.0       缺失数据  缺失数据  缺失数据                       缺失数据   \n",
       "\n",
       "   职业经历  \n",
       "0  缺失数据  \n",
       "1  缺失数据  \n",
       "2  缺失数据  \n",
       "3  缺失数据  \n",
       "4  缺失数据  \n",
       "5  缺失数据  \n",
       "6  缺失数据  \n",
       "7  缺失数据  \n",
       "8  缺失数据  \n",
       "9  缺失数据  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据清洗 - 去除空值\n",
    "# 文本型字段空值改为“缺失数据”，数字型字段空值改为 0 \n",
    "# 要求：创建函数\n",
    "# 提示：fillna方法填充缺失数据，注意inplace参数\n",
    "\n",
    "def data_cleaning(df):\n",
    "    cols = df.columns\n",
    "    for col in cols:\n",
    "        if df[col].dtype ==  'object':\n",
    "            df[col].fillna('缺失数据', inplace = True)\n",
    "        else:\n",
    "            df[col].fillna(0, inplace = True)\n",
    "    return(df)\n",
    "# 该函数可以将任意数据内空值替换\n",
    "\n",
    "data1_c = data_cleaning(data1)\n",
    "data1_c.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cuHE8+JtGHr15Xavlhx11AEccdSD9S+sZPr2q09o2VE2nsb405/rSsasoG7sq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\nEolEIpFIpED+D+30lhT76zB4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x97cbb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0UJO1rXz5EahemrW9Xb8daN9/x6ztsaqSVWWPAdBzWSWjR49mypQpzJ8/f806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\nOqFdezp1afgt/+IFc9ls2x3onv6P37X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SmonGdCQSiUQikUgkEolE\nIs0kGtORSCQSiUQikUgkEok0k2hMRyKRSCQSiUQikUgk0kyiMR2JRCKRSCQSiUQikUgzicZ0JBKJ\nRCKRSCQSiUQizSQa05FIJBKJRCKRSCQSiTSTaExHIpFIJBKJRCKRSCTSTKIxHYlEIpFIJBKJRCKR\nSDP5P+GSMGTUiROBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x983a668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 问题1 知友全国地域分布情况，分析出TOP20\n",
    "# 要求：\n",
    "# ① 按照地域统计 知友数量、知友密度（知友数量/城市常住人口），不要求创建函数\n",
    "# ② 知友数量，知友密度，标准化处理，取值0-100，要求创建函数\n",
    "# ③ 通过多系列柱状图，做图表可视化\n",
    "# 提示：\n",
    "# ① 标准化计算方法 = (X - Xmin) / (Xmax - Xmin)\n",
    "# ② 可自行设置图表风格\n",
    "\n",
    "df_city = data1_c.groupby('居住地').count()  # 按照居住地统计知友数量\n",
    "data2['city'] = data2['地区'].str[:-1]   # 城市信息清洗，去掉城市等级文字\n",
    "#print(df_city.head())  \n",
    "#print(data2.head())  \n",
    "\n",
    "q1data = pd.merge(df_city, data2, left_index = True, right_on = 'city', how = 'inner')[['_id','city','常住人口']]\n",
    "q1data['知友密度'] = q1data['_id']/q1data['常住人口'] \n",
    "#print(q1data.head())\n",
    "# 统计计算知友数量，知友密度\n",
    "\n",
    "def data_nor(df, *cols):\n",
    "    colnames = []\n",
    "    for col in cols:\n",
    "        colname = col + '_nor'\n",
    "        df[colname] = (df[col]-df[col].min())/(df[col].max()-df[col].min()) * 100\n",
    "        colnames.append(colname)\n",
    "    return(df,colnames)\n",
    "# 创建函数，结果返回标准化取值，新列列名\n",
    "\n",
    "resultdata = data_nor(q1data,'_id','知友密度')[0]\n",
    "resultcolnames = data_nor(q1data,'_id','知友密度')[1]\n",
    "q1data_top20_sl = resultdata.sort_values(resultcolnames[0], ascending=False)[['city',resultcolnames[0]]].iloc[:20]\n",
    "q1data_top20_md = resultdata.sort_values(resultcolnames[1], ascending=False)[['city',resultcolnames[1]]].iloc[:20]\n",
    "#print(q1data_top20_sl)\n",
    "# 标准化取值后得到知友数量，知友密度的TOP20数据\n",
    "\n",
    "fig1 = plt.figure(num=1,figsize=(12,4))\n",
    "y1 = q1data_top20_sl[resultcolnames[0]]\n",
    "plt.bar(range(20),\n",
    "        y1,\n",
    "        width = 0.8,\n",
    "        facecolor = 'yellowgreen',\n",
    "        edgecolor = 'k',\n",
    "        tick_label = q1data_top20_sl['city'])\n",
    "plt.title('知友数量TOP20\\n')\n",
    "plt.grid(True, linestyle = \"--\",color = \"gray\", linewidth = \"0.5\", axis = 'y')  \n",
    "for i,j in zip(range(20),y1):\n",
    "    plt.text(i+0.1,2,'%.1f' % j, color = 'k',fontsize = 9)\n",
    "\n",
    "fig2 = plt.figure(num=2,figsize=(12,4))\n",
    "y2 = q1data_top20_sl[resultcolnames[0]]\n",
    "plt.bar(range(20),\n",
    "        y2,\n",
    "        width = 0.8,\n",
    "        facecolor = 'lightskyblue',\n",
    "        edgecolor = 'k',\n",
    "        tick_label = q1data_top20_md['city'])\n",
    "plt.grid(True, linestyle = \"--\",color = \"gray\", linewidth = \"0.5\", axis = 'y')  \n",
    "plt.title('知友密度TOP20\\n')\n",
    "for i,j in zip(range(20),y2):\n",
    "    plt.text(i+0.1,2,'%.1f' % j, color = 'k',fontsize = 9)\n",
    "# 创建图表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vmzZtqFatWpSamlrqa0hNTSUDAwMaPHiwQlmbNm3I0NCQdu/eTdu3byd9fX3q1asX5eTk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\njTciIiIiIqIy4P8H2g961RNPZyAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9797358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 问题2 不同高校知友关注和被关注情况\n",
    "# 要求：\n",
    "# ① 按照学校（教育经历字段） 统计粉丝数（‘关注者’）、关注人数（‘关注’），并筛选出粉丝数TOP20的学校，不要求创建函数\n",
    "# ② 通过散点图 → 横坐标为关注人数，纵坐标为粉丝数，做图表可视化\n",
    "# ③ 散点图中，标记出平均关注人数（x参考线），平均粉丝数（y参考线）\n",
    "# 提示：\n",
    "# ① 可自行设置图表风格\n",
    "\n",
    "q2data = data1_c.groupby('教育经历').sum()[['关注','关注者']].drop(['缺失数据','大学','本科'])\n",
    "q2data_c = q2data.sort_values('关注',ascending=False)[:20]\n",
    "#print(q2data_c)\n",
    "# 统计计算学校的粉丝数、被关注量\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "x = q2data_c['关注']\n",
    "y = q2data_c['关注者']\n",
    "follow_mean = q2data_c['关注'].mean()\n",
    "fans_mean = q2data_c['关注者'].mean()\n",
    "plt.scatter(x,y,marker='.',\n",
    "           s = y/1000,\n",
    "           cmap = 'Blues',\n",
    "           c = y,\n",
    "           alpha = 0.8,\n",
    "           label = '学校')\n",
    "# 创建散点图\n",
    "\n",
    "plt.axvline(follow_mean,hold=None,label=\"平均关注人数：%i人\" % follow_mean,color='r',linestyle=\"--\",alpha=0.8)  # 添加x轴参考线\n",
    "plt.axhline(fans_mean,hold=None,label=\"平均粉丝数：%i人\" % fans_mean,color='g',linestyle=\"--\",alpha=0.8)   # 添加y轴参考线\n",
    "plt.legend(loc = 'upper left')\n",
    "plt.grid()\n",
    "# 添加显示内容\n",
    "\n",
    "for i,j,n in zip(x,y,q2data_c.index):\n",
    "    plt.text(i+500,j,n, color = 'k')\n",
    "# 添加注释"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
